ThruWire vs LangGraph
LangGraph helps engineers orchestrate long-running, stateful agents. ThruWire helps a software product own the customer work those agents advance.
The decision
This is usually a layer decision, not an either-or choice. Use LangGraph when you need low-level control over agent execution. Use ThruWire when your product must maintain a visible, domain-specific model of each customer’s work and keep it coherent as inputs change.
What LangGraph solves well
- Low-level graph orchestration for long-running, stateful agents.
- Durable execution, streaming, checkpoints, interrupts, and human-in-the-loop runtime control.
- Code-first application logic with explicit nodes, edges, state schemas, and recovery behavior.
What your product still needs to own
- The domain model for the larger job your customers are trying to complete.
- The durable goals, judgments, artifacts, dependencies, authority, and outcomes that outlive any graph run.
- The product experience through which your customers inspect, correct, approve, and redirect the work.
Product architecture
The framework can run the work. Your product still has to own it.
Where does the working model live?
LangGraph
LangGraph state lives in application-defined graph state and can be persisted through checkpoints and stores. Your team still defines the customer-facing domain model and product surface around it.
ThruWire
Inside your product, as a domain-specific model of each customer’s goals, evidence, decisions, artifacts, actions, and outcomes.
Does state survive the assistant and session?
LangGraph
It can. LangGraph supports checkpointed thread state and cross-thread stores when the application configures durable persistence.
ThruWire
The product-owned model persists across assistants, sessions, and model providers; an agent is a client of the work, not its container.
How do people steer the work?
LangGraph
Interrupts can pause execution for inspection, editing, approval, or input; the application supplies the customer experience.
ThruWire
Your customers inspect artifacts, evidence, changes, approvals, and open work in the same product surface the agent operates.
How do changes propagate?
LangGraph
Graph nodes, reducers, state updates, checkpoints, and replay determine execution. Domain-level invalidation remains application logic.
ThruWire
Explicit dependencies identify affected downstream work, preserve what remains valid, and selectively regenerate what became stale.
How they coexist
Keep LangGraph as the runtime for code-first agent loops. ThruWire can sit at the product layer above it: LangGraph executes the graph while ThruWire maintains the customer-owned artifacts, relationships, authority, and downstream consequences.
Technical sources
Apply the pattern
Map the work model your product should own and the role your existing agent stack should play.
Discuss your product →